I am now available to help with your Python machine learning projects. My specialties are Data Science, Data Analysis (inferential, descriptive), Data Visualization, Tensor Flow based Deep Learning, Pytorch based Deep Learning, and Python Machine Learning. Python and its IDE, frameworks, and libraries are all well-known to me. I have a number of online certifications in the same field. I have a number of conference and journal publications in the same domain.

As a data engineer, I've participated in the following projects:

1. Design and publication of Blind Image Quality Assessment using Gaussain Process Regression Algorithm.

2. Design and implementation of Reduced Reference Image Quality Assessment Algorithm using differential features and XGBOOST based regression algorithm. 

3. Deep learning based Novel perceptual quality assessment algorithm design and implantation.

4. Image Super Resolution

5. Low light Image Enhancement

6. Noisy image Enhancement

7. Image Restoration

8. Medical Image segmentation

9. Brain conntecome superresolution 

10. Image to Image Translation

11. Document clustering

12. BM-25 based search engine design

13. TF-IDF model design and implementation from scratch

14. Satellite Image Classification

15. Generative Adversarial network for image to image translation

16. COVID-19 Data Analysitics

17. Sociodemogrpahic study of effect of COVID-19 on the mental helalth of students

18. Transformer helath prediction

19. Sensor data prediction using LSTM based multi-time series network.

20. Man more

I can also manage any projects relating to the following:

Supervised learning, Unsupervised learning, Repetition learning (Classification,Regression,Clustering Related Projects)

CNN,CNN-with attention,RNNs, LSTM,GRU, Transformer Others (Experience with Time series analysis)

Object detection, face detection, and (Experience with Computer Vision and Deep Learning)

Moreover, I can manage any project connected to these:

Data Analysis (Pandas, Numpy,SCPIY Others)

Data Visualisation ( Matplotlib, Seaborn, Plotly)

Dimensionality Reduction ( PCA, LDA, Autoencoder )

Linear Regression, Logistic Regression, Decision Tree, Support Vector Machine, Naive Bayes, K-Nearest Neighbours, Random Forest, Gaussian Process, and Gradient Boosting regression, and classification Variants

Frameworks:

Jupyter Notebook

Pycharm

Google Colab

Spyder

PaperSpace